add support for scored named queries #11626
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Signed-off-by: Dharin Shah <[email protected]>
Signed-off-by: Dharin Shah <[email protected]>
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❌ Gradle check result for 16b7c19: FAILURE Please examine the workflow log, locate, and copy-paste the failure(s) below, then iterate to green. Is the failure a flaky test unrelated to your change? |
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❌ Gradle check result for 3aef42e: FAILURE Please examine the workflow log, locate, and copy-paste the failure(s) below, then iterate to green. Is the failure a flaky test unrelated to your change? |
Compatibility status:Checks if related components are compatible with change 9920c36 Incompatible componentsIncompatible components: [https://github.com/opensearch-project/performance-analyzer-rca.git, https://github.com/opensearch-project/performance-analyzer.git] Skipped componentsCompatible componentsCompatible components: [https://github.com/opensearch-project/custom-codecs.git, https://github.com/opensearch-project/observability.git, https://github.com/opensearch-project/job-scheduler.git, https://github.com/opensearch-project/flow-framework.git, https://github.com/opensearch-project/cross-cluster-replication.git, https://github.com/opensearch-project/geospatial.git, https://github.com/opensearch-project/opensearch-oci-object-storage.git, https://github.com/opensearch-project/k-nn.git, https://github.com/opensearch-project/sql.git, https://github.com/opensearch-project/neural-search.git, https://github.com/opensearch-project/notifications.git, https://github.com/opensearch-project/security-analytics.git, https://github.com/opensearch-project/asynchronous-search.git, https://github.com/opensearch-project/ml-commons.git, https://github.com/opensearch-project/reporting.git, https://github.com/opensearch-project/anomaly-detection.git, https://github.com/opensearch-project/index-management.git, https://github.com/opensearch-project/common-utils.git, https://github.com/opensearch-project/alerting.git, https://github.com/opensearch-project/security.git] |
Signed-off-by: Dharin Shah <[email protected]>
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Signed-off-by: Dharin Shah <[email protected]>
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❕ Gradle check result for ffdf852: UNSTABLE
Please review all flaky tests that succeeded after retry and create an issue if one does not already exist to track the flaky failure. |
Signed-off-by: Dharin Shah <[email protected]>
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❌ Gradle check result for 2937d8e: FAILURE Please examine the workflow log, locate, and copy-paste the failure(s) below, then iterate to green. Is the failure a flaky test unrelated to your change? |
Signed-off-by: Dharin Shah <[email protected]>
|
❕ Gradle check result for 9920c36: UNSTABLE
Please review all flaky tests that succeeded after retry and create an issue if one does not already exist to track the flaky failure. |
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Sorry for the delay in getting back on this -- it looks good. Thanks a lot @Dharin-shah!
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The backport to To backport manually, run these commands in your terminal: # Navigate to the root of your repository
cd $(git rev-parse --show-toplevel)
# Fetch latest updates from GitHub
git fetch
# Create a new working tree
git worktree add ../.worktrees/OpenSearch/backport-2.x 2.x
# Navigate to the new working tree
pushd ../.worktrees/OpenSearch/backport-2.x
# Create a new branch
git switch --create backport/backport-11626-to-2.x
# Cherry-pick the merged commit of this pull request and resolve the conflicts
git cherry-pick -x --mainline 1 52b27f47bca5b3ab52cab237542f32c307d203b4
# Push it to GitHub
git push --set-upstream origin backport/backport-11626-to-2.x
# Go back to the original working tree
popd
# Delete the working tree
git worktree remove ../.worktrees/OpenSearch/backport-2.xThen, create a pull request where the |
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@Dharin-shah could you please backport to |
Opensearch already support labelling the queries, that returns as a list in the returned results, of which query it matched. However one of the use case while doing hybrid search with query text and dense vector is to determine individual scores for each query type. This is very useful in further analysis and building offline model to generate better weights for ranking score. Hence adding this feature that sends the client to add the score for each matched query. --------- Signed-off-by: Dharin Shah <[email protected]> Signed-off-by: Dharin Shah <[email protected]> Co-authored-by: Dharin Shah <[email protected]> (cherry picked from commit 52b27f4)
Opensearch already support labelling the queries, that returns as a list in the returned results, of which query it matched. However one of the use case while doing hybrid search with query text and dense vector is to determine individual scores for each query type. This is very useful in further analysis and building offline model to generate better weights for ranking score. Hence adding this feature that sends the client to add the score for each matched query. --------- Signed-off-by: Dharin Shah <[email protected]> Signed-off-by: Dharin Shah <[email protected]> Co-authored-by: Dharin Shah <[email protected]> (cherry picked from commit 52b27f4) Signed-off-by: Andrew Ross <[email protected]>
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@reta @Dharin-shah I've opened the backport in #12427 |
* Add support for scored named queries (#11626) Opensearch already support labelling the queries, that returns as a list in the returned results, of which query it matched. However one of the use case while doing hybrid search with query text and dense vector is to determine individual scores for each query type. This is very useful in further analysis and building offline model to generate better weights for ranking score. Hence adding this feature that sends the client to add the score for each matched query. --------- Signed-off-by: Dharin Shah <[email protected]> Signed-off-by: Dharin Shah <[email protected]> Co-authored-by: Dharin Shah <[email protected]> (cherry picked from commit 52b27f4) Signed-off-by: Andrew Ross <[email protected]> * Update version checks Signed-off-by: Andrew Ross <[email protected]> * Update test version guard Co-authored-by: Andriy Redko <[email protected]> Signed-off-by: Andrew Ross <[email protected]> --------- Signed-off-by: Dharin Shah <[email protected]> Signed-off-by: Dharin Shah <[email protected]> Signed-off-by: Andrew Ross <[email protected]> Co-authored-by: Dharin Shah <[email protected]> Co-authored-by: Dharin Shah <[email protected]> Co-authored-by: Andriy Redko <[email protected]>
Opensearch already support labelling the queries, that returns as a list in the returned results, of which query it matched. However one of the use case while doing hybrid search with query text and dense vector is to determine individual scores for each query type. This is very useful in further analysis and building offline model to generate better weights for ranking score. Hence adding this feature that sends the client to add the score for each matched query. --------- Signed-off-by: Dharin Shah <[email protected]> Signed-off-by: Dharin Shah <[email protected]> Co-authored-by: Dharin Shah <[email protected]>
Opensearch already support labelling the queries, that returns as a list in the returned results, of which query it matched. However one of the use case while doing hybrid search with query text and dense vector is to determine individual scores for each query type. This is very useful in further analysis and building offline model to generate better weights for ranking score. Hence adding this feature that sends the client to add the score for each matched query. --------- Signed-off-by: Dharin Shah <[email protected]> Signed-off-by: Dharin Shah <[email protected]> Co-authored-by: Dharin Shah <[email protected]>
Opensearch already support labelling the queries, that returns as a list in the returned results, of which query it matched. However one of the use case while doing hybrid search with query text and dense vector is to determine individual scores for each query type. This is very useful in further analysis and building offline model to generate better weights for ranking score. Hence adding this feature that sends the client to add the score for each matched query. --------- Signed-off-by: Dharin Shah <[email protected]> Signed-off-by: Dharin Shah <[email protected]> Co-authored-by: Dharin Shah <[email protected]> Signed-off-by: Shivansh Arora <[email protected]>
Description
Opensearch already support labelling the queries, that returns as a list in the returned results, of which query it matched. However one of the use case while doing hybrid search with query text and dense vector is to determine individual scores for each query type. At GetYourGuide, this is very useful in further analysis and building offline model to generate better weights for ranking score. Hence adding this feature that sends the client to add the score for each matched query.
Related Issues
Resolves #[Issue number to be closed when this PR is merged]
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